Overview:

The authorities need to make an accurate assessment, so that they can avoid releasing the infected individuals and quarantining the non-infected ones.

Suppose a diagnostic test was ordered and was reported as positive. Based on the single test outcome, could it be reliably concluded that the individual was infected and counted in statistics as such? If the test was negative could the individual be declared infection-free and let go? Should population mass testing be mandated? What decision on further action should be made by the authorities based on the population mass testing results?

Why should you Attend:
One should attend this webinar to understand how to apply Bayesian inference methodology to correctly interpret the outcome of single and repeated positive or negative tests. Specifically, based on the single test outcome, could it be reliably concluded that the individual was infected and counted in statistics as such? If the test was negative could the individual be declared infection-free and let go? Should population mass testing be mandated? What decision on further action should be made by the authorities based on the population mass testing results?

Areas Covered in the Session:

• Bayesian interpretation of a single diagnostic test
• Bayesian interpretation of two and more consecutive repeated tests
• Positive and negative predictive values
• Two types of tests for COVID: real-time reverse transcriptase (RT-PCR) and a rapid antigen test (Ag-RDTs)
• The concept of test’s specificity and sensitivity
• Repeated tests with updated priors (prevalence)

• Nursing Managers
• Chief Nursing Officers
• Directors and VPs